Use game elements in Moodle courses to build learner resilience and motivationAbout This BookFormulate a Moodle course that acts as a flexible framework ready for your own contentKeep learners engrossed and create opportunities for motivation through the concepts of status, access, and powerA resourceful guide to innovative learning using automatic reports, assessments, and conditional release of activities Who This Book Is For This book has been designed for teachers who to use technology to create more engaging learning experiences for both online learning and in face-to-face sessions. This book will especially appeal to people who are interested in the underlying mechanics of play and games and want to know more about applying these concepts in an educational context. It is assumed that you are a teacher and expert in your field, have basic computer skills, and have access to the Internet.What You Will LearnSet up a scoring system using Moodle GradebookEnable communication and collaboration in your class as a Learning Community using forumsAssess your learners’ abilities by setting up challenges and questsConfigure gateways to check and ensure progress before new content or activities are releasedCreate Moodle assignments to provide effective feedback through a comment bank and custom scaleIssue Open Badges to recognize achievements and set up an online backpack to share digital badgesReduce anxiety for learners by using the game-like concept of “Levelling Up” In Detail This book describes how teachers can use Gamification design within the Moodle Learning Management System. Game elements can be included in course design by using, badges, rubrics, custom grading scales, forums, and conditional activities. Moodle courses do not have to be solo-learning experiences that replicate Distance Education models. The Gamification design process starts by profiling players and creating levels of achievement towards meeting learning outcomes. Each task is defined, valued, and sequenced. Motivation loops are devised to keep the momentum going. In a gaming studio, this approach would require a team of specialists with a large budget and time frames. Preparing for a class rarely has these optimal conditions. The approach used in this book is to introduce game elements into the course design gradually. First, apply gamification to just one lesson and then build up to gamifying a series of lessons over a term. Each example will indicate the difficulty level and time investment. Try it out to see what is most effective with your learners and choose wisely in your use of technology. By the end of this book, you will be able to create Moodle courses that incorporate choice, communication, challenge, and creativity.Style and approach An easy-to-follow guide full of screenshots and step-by-step instructions with estimated time frames required to accomplish numerous tasks. Tips are offered for new Moodlers and plugin extensions are suggested for advanced Moodlers. The focus of the book is on why you would want to use each activity rather than detailed technical de*ions.

Create robust and maintainable Java applications using the functional style of programmingAbout This BookExplore how you can blend object-oriented and functional programming styles in JavaUse lambda expressions to write flexible and succinct codeA tutorial that strengthens your fundamentals in functional programming techniques to enhance your applications Who This Book Is For If you are a Java developer with object-oriented experience and want to use a functional programming approach in your applications, then this book is for you. All you need to get started is familiarity with basic Java object-oriented programming concepts.What You Will LearnUse lambda expressions to simplyfy codeUse function composition to achieve code fluencyApply streams to simply implementations and achieve parallelismIncorporate recursion to support an application’s functionalityProvide more robust implementations using OptionalsImplement design patterns with less codeRefactor object-oriented code to create a functional solutionUse debugging and testing techniques specific to functional programs In Detail Functional programming is an increasingly popular technology that allows you to simplify many tasks that are often cumbersome and awkward using an object-oriented approach. It is important to understand this approach and know how and when to apply it. Functional programming requires a different mindset, but once mastered it can be very rewarding. This book simplifies the learning process as a problem is described followed by its implementation using an object-oriented approach and then a solution is provided using appropriate functional programming techniques. Writing succinct and maintainable code is facilitated by many functional programming techniques including lambda expressions and streams. In this book, you will see numerous examples of how these techniques can be applied starting with an introduction to lambda expressions. Next, you will see how they can replace older approaches and be combined to achieve surprisingly elegant solutions to problems. This is followed by the investigation of related concepts such as the Optional class and monads, which offer an additional approach to handle problems. Design patterns have been instrumental in solving common problems. You will learn how these are enhanced with functional techniques. To transition from an object-oriented approach to a functional one, it is useful to have IDE support. IDE tools to refactor, debug, and test functional programs are demonstrated through the chapters. The end of the book brings together many of these functional programming techniques to create a more comprehensive application. You will find this book a very useful resource to learn and apply functional programming techniques in Java.Style and approach In this tutorial, each chapter starts with an introduction to the terms and concepts covered in that chapter. It quickly progresses to contrast an object-oriented approach with a functional approach using numerous code examples.

Harness the power of OpenStack Networking for public and private clouds using 90 hands-on recipesAbout This BookBuild and manage virtual switching, routing, and firewall-based networks in OpenStack using NeutronDevelop plugins and drivers for Neutron to enhance the built-in networking capabilitiesMonitor and automate OpenStack networks using tools like Ceilometer and Heat Who This Book Is For This book is aimed at network and system administrators who want to deploy and manage OpenStack-based cloud and IT infrastructure. If you have basic knowledge of OpenStack and virtualization, this book will help you leverage the rich functionality of OpenStack Networking in your cloud deployments.What You Will LearnOperate OpenStack Networking for public and private cloudsConfigure advanced routing services for your workloadsSecure data traffic using firewall-as-a-service capabilities of OpenStackDiscover how to leverage VXLAN to implement SDN in your OpenStack cloudMonitor the virtual networks using CeilometerDevelop plugins to enhance and customize OpenStack NetworkingProvide HA and VPN connectivity for your virtual machinesTroubleshoot and solve common problems with OpenStack Networking In Detail Networking in OpenStack has evolved from Nova Network to Neutron. This has resulted in a rich suite of networking services available to OpenStack users and administrators. Advanced services such as routers, firewall, and load balancers use building blocks such as network and subnets. Recent improvements support powerful customization using plugins. The evolution of Neutron continues as it integrates with tools like Ceilometer and Heat. This book will explore the built-in capabilities of Neutron to effectively deploy cloud solutions. You will begin with the most fundamental constructs of OpenStack Networking for switching and routing. You will then learn how to provide your tenants with services like firewalls and load-balancers. The step-by-step recipes will help you configure and troubleshoot networking problems in your cloud. This book will also introduce you to advanced topics like Ceilometer, Heat, and other upcoming tools in OpenStackStyle and approach The book is full of step-by-step recipes to configure and manage the networking aspects of your OpenStack cloud. In addition to covering basic configuration involved in OpenStack Networking, the books also shares various troubleshooting tips and techniques. As much as possible the book uses OpenStack dashboard (Horizon) to help the user get a feel of real OpenStack Networking

Build real-world, industry-strength data storage solutions with time-tested design methodologies using CassandraAbout This BookExplore design patterns which co-exist with legacy data stores, migration from RDBMS, and caching technologies with CassandraLearn about design patterns and use Cassandra to provide consistency, availability, and partition tolerance guarantees for applicationsHandle temporal data for analytical purposes Who This Book Is For This book is intended for big data developers who are familiar with the basics of Cassandra and wish to understand and utilize Cassandra design patterns to develop real-world big data solutions. Prior knowledge of RDBMS solutions is assumed.What You Will LearnEnable Cassandra to co-exist with RDBMS and other legacy data storesExplore various design patterns to build effective and robust storage solutionsMigrate from RDBMS-based data stores and caching solutions to CassandraUnderstand the behaviour of Cassandra when trying to balance the needs of consistency, availability, and partition toleranceDeal with time stamps related to data effectivelySee how Cassandra can be used in analytical use casesApply the design patterns covered in this book in real-world use cases In Detail There are many NoSQL data stores used by big data applications. Cassandra is one of the most widely used NoSQL data stores that is frequently used by a huge number of heavy duty Internet-scale applications. Unlike the RDBMS world, the NoSQL landscape is very diverse and there is no one way to model data stores. This mandates the need to have good solutions to commonly seen data store design problems. Cassandra addresses such common problems simply. If you are new to Cassandra but well-versed in RDBMS modeling and design, then it is natural to model data in the same way in Cassandra, resulting in poorly performing applications and losing the real purpose of Cassandra. If you want to learn to make the most of Cassandra, this book is for you. This book starts with strategies to integrate Cassandra with other legacy data stores and progresses to the ways in which a migration from RDBMS to Cassandra can be accomplished. The journey continues with ideas to migrate data from cache solutions to Cassandra. With this, the stage is set and the book moves on to some of the most commonly seen problems in applications when dealing with consistency, availability, and partition tolerance guarantees. Cassandra is exceptionally good at dealing with temporal data and patterns such as the time-series pattern and log pattern, which are covered next. Many NoSQL data stores fail miserably when a huge amount of data is read for analytical purposes, but Cassandra is different in this regard. Keeping analytical needs in mind, you’ll walk through different and interesting design patterns. No theoretical discussions are complete without a good set of use cases to which the knowledge gained can be applied, so the book concludes with a set of use cases you can apply the patterns you’ve learned.Style and approach This book is written in very simple language and an engaging style complete with examples in every chapter and real-world use cases at the end of the book.

Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipesAbout This BookImplement Scala in your data analysis using features from Spark, Breeze, and ZeppelinScale up your data anlytics infrastructure with practical recipes for Scala machine learningRecipes for every stage of the data analysis process, from reading and collecting data to distributed analytics Who This Book Is For This book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis.What You Will LearnFamiliarize and set up the Breeze and Spark libraries and use data structuresImport data from a host of possible sources and create dataframes from CSVClean, validate and transform data using Scala to pre-process numerical and string dataIntegrate quintessential machine learning algorithms using Scala stackBundle and scale up Spark jobs by deploying them into a variety of cluster managersRun streaming and graph analytics in Spark to visualize data, enabling exploratory analysis In Detail This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.Style and approach This book contains a rich set of recipes that covers the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala and Spark.

Generate effective results in a variety of visually appealing charts using the plotting packages in PythonAbout This BookExplore various tools and their strengths while building meaningful representations that can make it easier to understand dataPacked with computational methods and algorithms in diverse fields of scienceWritten in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed.What You Will LearnGather, cleanse, access, and map data to a visual frameworkRecognize which visualization method is applicable and learn best practices for data visualizationGet acquainted with reader-driven narratives and author-driven narratives and the principles of perceptionUnderstand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with itExplore with various visualization choices how Python can be very useful in computation in the field of finance and statisticsGet to know why Python is the second choice after Java, and is used frequently in the field of machine learningCompare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.jsDiscover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems.Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Over 90 practical and highly applicable recipes to successfully deploy various OpenStack configurations in productionAbout This BookGet a deep understanding of OpenStack’s internal structure and servicesLearn real-world examples on how to build and configure various production grade use cases for each of OpenStack's servicesUse a step-by-step approach to install and configure OpenStack’s services to provide Compute, Storage, and Networking as a services for cloud workloads Who This Book Is For If you have a basic understanding of Linux and Cloud computing and want to learn about configurations that OpenStack supports, this is the book for you. Knowledge of virtualization and managing Linux environments is expected. Prior knowledge or experience of OpenStack is not required, although beneficial.What You Will LearnPlan an installation of OpenStack with a basic configurationDeploy OpenStack in a highly available configurationConfigure Keystone Identity services with multiple types of identity backendsConfigure Glance Image Store with File, NFS, Swift, or Ceph image backends and use local image cachingDesign Cinder to use a single storage provider such as LVM, Ceph, and NFS backends, or to use multiple storage backends simultaneouslyManage and configure the OpenStack networking backendConfigure OpenStack's compute hypervisor and the instance scheduling mechanismBuild and customize the OpenStack dashboard In Detail OpenStack is the most popular open source cloud platform used by organizations building internal private clouds and by public cloud providers. OpenStack is designed in a fully distributed architecture to provide Infrastructure as a Service, allowing us to maintain a massively scalable cloud infrastructure. OpenStack is developed by a vibrant community of open source developers who come from the largest software companies in the world. The book provides a comprehensive and practical guide to the multiple uses cases and configurations that OpenStack supports. This book simplifies the learning process by guiding you through how to install OpenStack in a single controller configuration. The book goes deeper into deploying OpenStack in a highly available configuration. You’ll then configure Keystone Identity Services using LDAP, Active Directory, or the MySQL identity provider and configure a caching layer and SSL. After that, you will configure storage back-end providers for Glance and Cinder, which will include Ceph, NFS, Swift, and local storage. Then you will configure the Neutron networking service with provider network VLANs, and tenant network VXLAN and GRE. Also, you will configure Nova’s Hypervisor with KVM, and QEMU emulation, and you will configure Nova’s scheduler filters and weights. Finally, you will configure Horizon to use Apache HTTPD and SSL, and you will customize the dashboard’s appearance.Style and approach This book consists of clear, concise instructions coupled with practical and applicable recipes that will enable you to use and implement the latest features of OpenStack.

Master machine learning techniques with R to deliver insights for complex projectsAbout This BookGet to grips with the application of Machine Learning methods using an extensive set of R packagesUnderstand the benefits and potential pitfalls of using machine learning methodsImplement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will LearnGain deep insights to learn the applications of machine learning tools to the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisFamiliarize yourself with fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesRealize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.

Accelerate your code writing skills with over twenty programming patterns that will make your code easier to maintain and scaleAbout This BookOptimize your web application for production useBuild views and controllers with minimal effort that will evolve with your applicationLearn how to maintain a MeteorJS project while it is running in production Who This Book Is For This book is for developers who have already had an introductory course with Meteor. Basic knowledge of web development is recommended.What You Will LearnUse of Jade, Stylus, and CoffeeScript to speed up web developmentIncrease productivity by leveraging the best packages in the communityOptimize your site for load speed with advanced publishers and subscribersLeverage the aggregation framework to produce results with big dataMaster the intricacies of front-end development using Jeet, Bootstrap, CSS animations, and moreOptimize your site for search engine visibilitySecure your site with Meteor’s best practicesTrack the live status of your application, ensuring all errors have been taken care of In Detail With the increasing interest in NodeJS web applications, a new framework, Meteor, has joined the ranks to simplify developer workflows. Meteor is one of the few open source frameworks that has received funding since its early development stages. It builds on ideas from existing frameworks and libraries, offering developers an easy way to develop a prototype app. At the same time, it gives them the tools and flexibility to build a fully fledged production app. Meteor is the weapon of choice for start-ups in today’s world. Meteor Design Patterns cuts through the jargon that most websites play with and gets to the point with simple solutions that will boost your development skills. We start off with a refresher on the basics of JavaScript programming such as templates, CoffeeScript, the Event Loop, and the Merge Box, amongst others. You then learn how to map real-world data and optimize the data’s publishers to output data with the least amount of work done by the server with some subscribe and publish patterns. Next, using front-end patterns, you will learn how to create maintainable and trackable forms, and make our site crawlable by any search engine. Following this, you will see how to optimize and secure the web application and maintain applications without breaking other features. Finally, you will learn how to deploy a secure production-ready application while learning to set up modulus, compose with Oplog tracking and SSL certificates, as well as error tracking with Kadira. Throughout the book, you will put your skills to practice and build an online shop from scratch. By the end of the book, you will have built a feature-rich online shop.Style and approach The book is a practical handbook on how to build an e-commerce web app using Meteor. Every topic ties into the webapp to easily illustrate the concepts that you are learning about.

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problemsAbout This BookUnderstand the principles of Bayesian Inference with less mathematical equationsLearn state-of-the art Machine Learning methodsFamiliarize yourself with the recent advances in Deep Learning and Big Data frameworks with this step-by-step guide Who This Book Is For This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications. To understand this book, it would be useful if you have basic knowledge of probability theory and analytics and some familiarity with the programming language R.What You Will LearnSet up the R environmentCreate a classification model to predict and explore discrete variablesGet acquainted with Probability Theory to analyze random eventsBuild Linear Regression modelsUse Bayesian networks to infer the probability distribution of decision variables in a problemModel a problem using Bayesian Linear Regression approach with the R package BLRUse Bayesian Logistic Regression model to classify numerical dataPerform Bayesian Inference on massively large data sets using the MapReduce programs in R and Cloud computing In Detail Bayesian Inference provides a unified framework to deal with all sorts of uncertainties when learning patterns form data using machine learning models and use it for predicting future observations. However, learning and implementing Bayesian models is not easy for data science practitioners due to the level of mathematical treatment involved. Also, applying Bayesian methods to real-world problems requires high computational resources. With the recent advances in computation and several open sources packages available in R, Bayesian modeling has become more feasible to use for practical applications today. Therefore, it would be advantageous for all data scientists and engineers to understand Bayesian methods and apply them in their projects to achieve better results. Learning Bayesian Models with R starts by giving you a comprehensive coverage of the Bayesian Machine Learning models and the R packages that implement them. It begins with an introduction to the fundamentals of probability theory and R programming for those who are new to the subject. Then the book covers some of the important machine learning methods, both supervised and unsupervised learning, implemented using Bayesian Inference and R. Every chapter begins with a theoretical de*ion of the method explained in a very simple manner. Then, relevant R packages are discussed and some illustrations using data sets from the UCI Machine Learning repository are given. Each chapter ends with some simple exercises for you to get hands-on experience of the concepts and R packages discussed in the chapter. The last chapters are devoted to the latest development in the field, specifically Deep Learning, which uses a class of Neural Network models that are currently at the frontier of Artificial Intelligence. The book concludes with the application of Bayesian methods on Big Data using the Hadoop and Spark frameworks.Style and approach The book first gives you a theoretical de*ion of the Bayesian models in simple language, followed by details of its implementation in the R package. Each chapter has illustrations for the use of Bayesian model and the corresponding R package, using data sets from the UCI Machine Learning repository. Each chapter also contains sufficient exercises for you to get more hands-on practice.

The ultimate troubleshooting guide for clear, concise, and real-world solutions to a wide range of common Citrix XenDesktop problemsAbout This BookExplore the XenDesktop architecture and work with various troubleshooting tools that every Citrix admin should know aboutDiscover how to troubleshoot performance, VDA registration, and NetScaler integration issuesA fast-paced troubleshooting guide to help you identify and resolve any kind of problem you might face while working with Citrix XenDesktop Who This Book Is For Troubleshooting Citrix XenDesktop is targeted at Citrix Administrators or Citrix Engineers who are working on Xendesktop and want to learn tips and techniques required to deal with the issues they face in their day-to-day life. A working knowledge of core elements and concepts of Xendesktop would be an added advantage.What You Will LearnSolve VDA registration problems and Citrix session launch difficultiesIdentify and resolve XenDesktop service issuesTroubleshoot performance issues related to the XenDesktop architectureWork around common printing issuesUnderstand the Citrix XenDesktop HDX policies and deal with the HDX MediaStream challengesResolve the common MCS and PVS configuration issues in your XenDesktop environmentFind solutions to some general issues that have been identified and recorded by Citrix in their database that every administrator must be aware of In Detail In today’s world, many organizations have decided to move to secure and stable VDI platforms to benefit their organization to meet their security needs. To meet an organization’s requirements, Citrix XenDesktop serves as the best desktop virtualization solution available, providing the optimum user experience. Troubleshooting Citrix XenDesktop is a single resource guide that will help you dig deep into all the technical issues you encounter to resolve them using an autonomous and well-defined approach. The book starts by walking you through the XenDesktop architecture and the troubleshooting toolkit for Citrix XenDesktop. The subsequent chapters will help you identify possible causes of various types of Citrix XenDesktop problems that may arise while installing, configuring, or troubleshooting day-to-day problems. You will also be dealing with the most common and important VDA registration problems that you might often face while working with the XenDesktop product suite. Additionally, you will resolve issues that arise while launching Citrix sessions, troubleshoot performance issues, and learn how to integrate Citrix NetScaler with your XenDesktop environment.Style and approach This book is an easy-to-follow troubleshooting guide with real-world examples of resolving XenDesktop issues. Each chapter is focused on a specific troubleshooting area, giving you the time to learn about and apply relevant tools and practices to troubleshoot the problems using a systematic approach.

Exploit the power of dynamic cloud formation and auto-scaling features to fully implement OpenStack orchestrationAbout This BookSet up, manage, and troubleshoot Heat and effectively automate your datacenter and cloud-based servicesAchieve high availability, minimize down-time, and automate the deployment of cloud-based services and resources with minimum effortUpgrade your skills and manipulate resources on virtual machines in an unattended fashion using Heat Who This Book Is For If you are a System Engineer, System Administrator, Cloud Administrator, or a Cloud Engineer, then this book is for you. You should have a background of working in a Linux-based setup. Any knowledge of OpenStack-based cloud infrastructure will help you create wonders using this book.What You Will LearnInstall an orchestration service for a private cloud environmentTackle errors that show up during the installation and configuration of heatConfigure a template for orchestration using the native HOT formatConfigure a template for orchestration using the AWS cloud formation formatDeploy a stack using the HOT templateDeploy a test stack using the AWS CloudFormation templateAutomate and orchestrate cloud-based services with OpenStack Heat In Detail This book is focused on setting up and using one of the most important services in OpenStack orchestration, Heat. First, the book introduces you to the orchestration service for OpenStack to help you understand the uses of the templating mechanism, complex control groups of cloud resources, and huge-potential and multiple-use cases. We then move on to the topology and orchestration specification for cloud applications and standards, before introducing the most popular IaaS cloud framework, Heat. You will get to grips with the standards used in Heat, overview and roadmap, architecture and CLI, heat API, heat engine, CloudWatch API, scaling principles, JeOS and installation and configuration of Heat. We wrap up by giving you some insights into troubleshooting for OpenStack. With easy-to-follow, step-by-step instructions and supporting images, you will be able to manage OpenStack operations by implementing the orchestration services of Heat.Style and approach The book is a step-by-step guide to implementing an orchestration (cloud formation) service for OpenStack-based cloud environments. This book uses real-world scenarios and examples to demonstrate the procedures in an easy-to-understand language with plenty of screenshots to help you get a better understanding.

A hands-on guide to building an enterprise-grade, scalable RESTful web service using the Spring FrameworkAbout This BookFollow best practices and explore techniques such as clustering and caching to achieve a scalable web serviceLeverage the Spring Framework to quickly implement RESTful endpointsLearn to implement a client library for a RESTful web service using the Spring Framework Who This Book Is For This book is intended for those who want to learn to build RESTful web services with the Spring Framework. To make best use of the code samples included in the book, you should have a basic knowledge of the Java language. Previous experience with the Spring Framework would also help you get up and running quickly.What You Will LearnDeep dive into the principles behind RESTExpose CRUD operations through RESTful endpoints with the Spring FrameworkDevise response formats and error handling strategies, offering a consistent and flexible structure to simplify integration for service consumersFollow the best approaches for dealing with a service’s evolution while maintaining backward compatibilityUnderstand techniques to secure web servicesComply with the best ways to test RESTful web services, including tips for load testingOptimise and scale web services using techniques such as caching and clustering In Detail REST is an architectural style that tackles the challenges of building scalable web services. In today’s connected world, APIs have taken a central role on the web. APIs provide the fabric through which systems interact, and REST has become synonymous with APIs. The depth, breadth, and ease of use of Spring makes it one of the most attractive frameworks in the Java ecosystem. Marrying the two technologies is therefore a very natural choice. This book takes you through the design of RESTful web services and leverages the Spring Framework to implement these services. Starting from the basics of the philosophy behind REST, you’ll go through the steps of designing and implementing an enterprise-grade RESTful web service. Taking a practical approach, each chapter provides code samples that you can apply to your own circumstances. This book goes beyond the use of Spring and explores approaches to tackle resilience, security, and scalability concerns. You’ll learn techniques to deal with security in Spring and discover how to implement unit and integration test strategies. Finally, the book ends by walking you through building a Java client for your RESTful web service, along with some scaling techniques for it.Style and approach This book is a step-by-step, hands-on guide to designing and building RESTful web services. The book follows the natural cycle of developing these services and includes multiple code samples to help you.

Sharpen your skills in Swift by designing and deploying seven fully functional applicationsAbout This BookDevelop a variety of iOS-compatible applications that range from health and fitness to utilities using this project-based handbookDiscover ways to make the best use of the latest features in Swift to build on a wide array of applicationsFollow step-by-step instructions to create Swift apps oriented for the real world Who This Book Is For If you are a competent iOS developer who wants to develop stunning applications with Swift, then this book is for you. Familiarity with Swift programming is assumed.What You Will LearnGet to grips with the basics of Xcode and Swift for application developmentCreate a Photo Sharing application to capture an image, edit it using different features and share it via social media.Develop applications using the WatchKit and exchange data between iPhone and the WatchUse advanced features such as SpriteKit to build a gameInstall third-party Swift frameworks to improvise on your application developmentDiscover how to simulate home automation with HomeKitBuild an application to monitor the user's weight, heart rate and the number of steps for Health Historic AnalysisManipulate media using AVFoundation framework to merge audio and video. In Detail In this book, you will work through seven different projects to get you hands-on with developing amazing applications for iOS devices. We start off with a project that teaches you how to build a utility app using Swift. Moving on, we cover the concepts behind developing an entertainment or social networking related application, for example, a small application that helps you to share images, audio, and video files from one device to another. You’ll also be guided through create a city information app with customized table views, a reminder app for the Apple Watch, and a game app using SpriteKit. By the end of this book, you will have the required skillset to develop various types of iOS applications with Swift that can run on different iOS devices. You will also be well versed with complex techniques that can be used to enhance the performance of your applications.Style and approach This book takes a step-by-step approach to help you build apps from scratch and learn the methodology to develop real-time applications using Swift.

Manage, analyze, and visualize data with Microsoft Excel 2013 to transform raw data into ready to use informationAbout This BookCreate formulas to help you analyze and explain findingsDevelop interactive spreadsheets that will impress your audience and give them the ability to slice and dice dataA step-by-step guide to learn various ways to model data for businesses with the help of Excel 2013 Who This Book Is For If you want to start using Excel 2013 for data analysis and business modeling and enhance your skills in the data analysis life cycle then this book is for you, whether you’re new to Excel or experienced.What You Will LearnDiscover what Excel formulas are all about and how to use them in your spreadsheet developmentIdentify bad data and learn cleaning strategiesCreate interactive spreadsheets that engage and appeal to your audienceLeverage Excel’s powerful built-in tools to get the median, maximum, and minimum values of your dataBuild impressive tables and combine datasets using Excel’s built-in functionalityLearn the powerful *ing language VBA, allowing you to implement your own custom solutions with ease In Detail Excel 2013 is one of the easiest to use data analysis tools you will ever come across. Its simplicity and powerful features has made it the go to tool for all your data needs. Complex operations with Excel, such as creating charts and graphs, visualization, and analyzing data make it a great tool for managers, data scientists, financial data analysts, and those who work closely with data. Learning data analysis and will help you bring your data skills to the next level. This book starts by walking you through creating your own data and bringing data into Excel from various sources. You’ll learn the basics of SQL syntax and how to connect it to a Microsoft SQL Server Database using Excel’s data connection tools. You will discover how to spot bad data and strategies to clean that data to make it useful to you. Next, you'll learn to create custom columns, identify key metrics, and make decisions based on business rules. You’ll create macros using VBA and use Excel 2013’s shiny new macros. Finally, at the end of the book, you'll be provided with useful shortcuts and tips, enabling you to do efficient data analysis and business modeling with Excel 2013.Style and approach This is a step-by-step guide to performing data analysis and business modelling with Excel 2013, complete with examples and tips.

The team behind the bestselling The Food52 Cookbook and the James Beard Award–winning website Food52.com are back. Powered by a thriving online community and edited by noted food writers Amanda Hesser and Merrill Stubbs, Food52.com spotlights the best recipes from talented home cooks all over the world. The Food52 Cookbook, Volume 2, features seventy-five of the latest community favorites, including:Late-Night Coffee-Brined Chicken Roasted Carrot Soup Herbed Beef Skewers with Horseradish Cream Kentucky Hot Toddy Burnt Caramel Pudding

At some point in our lives, many of us will face the crisis of an unexpected illness. For parents, the fear, anxiety and confusion resulting from a cancer diagnosis can be particularly devastating. When A Parent Has Cancer is a book for families written from the heart of experience. A mother, physician, and cancer survivor, Dr Wendy Harpham offers clear, direct, and sympathetic advice for parents challenged with the task of raising normal, healthy children while they struggle with a potentially life threatening disease. Dr Harpham lays the groundwork of her book with specific plans for helping children through the upheaval of a parent's diagnosis and treatment, remission and recovery, and if necessary, confronting the possibility of death. She emphasises the importance of being honest with children about the gravity of the illness, while assuring them that their basic needs will always be met. Included is Becky and the Worry Cup, an illustrated children's book that tells the story of a seven year old girl's experiences with her mother's cancer.

The recent financial crisis led to sweeping reforms that inspired countless references to the financial reforms of the New Deal. Comparable to the reforms of the New Deal in both scope and scale, the 2,300-page Dodd-Frank Act of 2010-the main regulatory reform package introduced in the United States-also shared with New Deal reforms the assumption that the underlying cause of the crisis was misbehavior by securities market participants, exacerbated by lax regulatory oversight.With Wasting a Crisis, Paul G. Mahoney offers persuasive research to show that this now almost universally accepted narrative of market failure-broadly similar across financial crises-is formulated by political actors hoping to deflect blame from prior policy errors. Drawing on a cache of data, from congressional investigations, litigation, regulatory reports, and filings to stock quotes from the 1920s and '30s, Mahoney moves beyond the received wisdom about the financial reforms of the New Deal, showing that lax regulation was not a substantial cause of the financial problems of the Great Depression. As new regulations were formed around this narrative of market failure, not only were the majority largely ineffective, they were also often counterproductive, consolidating market share in the hands of leading financial firms. An overview of twenty-first-century securities reforms from the same analytic perspective, including Dodd-Frank and the Sarbanes-Oxley Act of 2002, shows a similar pattern and suggests that they too may offer little benefit to investors and some measurable harm.

Making "e;Nature"e; is the first book to chronicle the foundation and development of Nature, one of the world's most influential scientific institutions. Now nearing its hundred and fiftieth year of publication, Nature is the international benchmark for scientific publication. Its contributors include Charles Darwin, Ernest Rutherford, and Stephen Hawking, and it has published many of the most important discoveries in the history of science, including articles on the structure of DNA, the discovery of the neutron, the first cloning of a mammal, and the human genome.But how did Nature become such an essential institutionIn Making "e;Nature,"e; Melinda Baldwin charts the rich history of this extraordinary publication from its foundation in 1869 to current debates about online publishing and open access. This pioneering study not only tells Nature's story but also sheds light on much larger questions about the history of science publishing, changes in scientific communication, and shifting notions of "e;scientific community."e; Nature, as Baldwin demonstrates, helped define what science is and what it means to be a scientist.

Secularism is usually thought to contain the project of self-deification, in which humans attack God's authority in order to take his place, freed from all constraints. Julie E. Cooper overturns this conception through an incisive analysis of the early modern justifications for secular politics. While she agrees that secularism is a means of empowerment, she argues that we have misunderstood the sources of secular empowerment and the kinds of strength to which it aspires.Contemporary understandings of secularism, Cooper contends, have been shaped by a limited understanding of it as a shift from vulnerability to power. But the works of the foundational thinkers of secularism tell a different story. Analyzing the writings of Hobbes, Spinoza, and Rousseau at the moment of secularity's inception, she shows that all three understood that acknowledging one's limitations was a condition of successful self-rule. And while all three invited humans to collectively build and sustain a political world, their invitations did not amount to self-deification. Cooper establishes that secular politics as originally conceived does not require a choice between power and vulnerability. Rather, it challenges us-today as then-to reconcile them both as essential components of our humanity.

The pigeon is the quintessential city bird. Domesticated thousands of years ago as a messenger and a source of food, its presence on our sidewalks is so common that people consider the bird a nuisance-if they notice it at all. Yet pigeons are also kept for pleasure, sport, and profit by people all over the world, from the "e;pigeon wars"e; waged by breeding enthusiasts in the skies over Brooklyn to the Million Dollar Pigeon Race held every year in South Africa.Drawing on more than three years of fieldwork across three continents, Colin Jerolmack traces our complex and often contradictory relationship with these versatile animals in public spaces such as Venice's Piazza San Marco and London's Trafalgar Square and in working-class and immigrant communities of pigeon breeders in New York and Berlin. By exploring what he calls "e;the social experience of animals,"e; Jerolmack shows how our interactions with pigeons offer surprising insights into city life, community, culture, and politics. Theoretically understated and accessible to interested readers of all stripes, The Global Pigeon is one of the best and most original ethnographies to be published in decades.